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  2. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    Database normalization is the process of structuring a relational database accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .

  3. Ellipsoid method - Wikipedia

    en.wikipedia.org/wiki/Ellipsoid_method

    Consider a family of convex optimization problems of the form: minimize f(x) s.t. x is in G, where f is a convex function and G is a convex set (a subset of an Euclidean space R n). Each problem p in the family is represented by a data-vector Data( p ), e.g., the real-valued coefficients in matrices and vectors representing the function f and ...

  4. Constrained optimization - Wikipedia

    en.wikipedia.org/wiki/Constrained_optimization

    For very simple problems, say a function of two variables subject to a single equality constraint, it is most practical to apply the method of substitution. [4] The idea is to substitute the constraint into the objective function to create a composite function that incorporates the effect of the constraint.

  5. Drift plus penalty - Wikipedia

    en.wikipedia.org/wiki/Drift_plus_penalty

    This constraint is written in standard form by defining a new penalty function y(t) = a(t) − b(t). The above problem seeks to minimize the time average of an abstract penalty function p'(t)'. This can be used to maximize the time average of some desirable reward function r(t) by defining p(t) = −r('t).

  6. Tuple relational calculus - Wikipedia

    en.wikipedia.org/wiki/Tuple_relational_calculus

    It formed the inspiration for the database-query languages QUEL and SQL, of which the latter, although far less faithful to the original relational model and calculus, is now the de facto standard database-query language; a dialect of SQL is used by nearly every relational-database-management system.

  7. Reduced cost - Wikipedia

    en.wikipedia.org/wiki/Reduced_cost

    Given a system minimize subject to ,, the reduced cost vector can be computed as , where is the dual cost vector. It follows directly that for a minimization problem, any non- basic variables at their lower bounds with strictly negative reduced costs are eligible to enter that basis, while any basic variables must have a reduced cost that is ...

  8. Puzzle solutions for Friday, Nov. 22, 2024

    www.aol.com/news/puzzle-solutions-friday-nov-22...

    Note: Most subscribers have some, but not all, of the puzzles that correspond to the following set of solutions for their local newspaper. CROSSWORDS

  9. Lagrange multiplier - Wikipedia

    en.wikipedia.org/wiki/Lagrange_multiplier

    For example, in economics the optimal profit to a player is calculated subject to a constrained space of actions, where a Lagrange multiplier is the change in the optimal value of the objective function (profit) due to the relaxation of a given constraint (e.g. through a change in income); in such a context is the marginal cost of the ...